Christiane Jablonowski and Diana Thatcher University of Michigan, Ann Arbor, USA Physics-Dynamics Coupling Workshop (PDC14), Ensenada, Mexico, 12/3/2014.

Slides:



Advertisements
Similar presentations
What’s quasi-equilibrium all about?
Advertisements

Thoughts on Climate Theory Based on collaborations with Wenyu Zhou, Dargan Frierson, Sarah Kang, Erica Staehling, Gang Chen, Steve Garner, Ming Zhao Isaac.
Moisture Transport in Baroclinic Waves Ian Boutle a, Stephen Belcher a, Bob Plant a Bob Beare b, Andy Brown c 24 April 2014.
A High-Order Finite-Volume Scheme for the Dynamical Core of Weather and Climate Models Christiane Jablonowski and Paul A. Ullrich, University of Michigan,
The Role of High-value Observations for Forecast Simulations in a Multi- scale Climate Modeling Framework Gabriel J. Kooperman, Michael S. Pritchard, and.
Data assimilation for validation of climate modeling systems Pierre Gauthier Department of Earth and Atmospheric Sciences Université du Québec à Montréal.
The Problem of Parameterization in Numerical Models METEO 6030 Xuanli Li University of Utah Department of Meteorology Spring 2005.
Günther Zängl, DWD1 Improvements for idealized simulations with the COSMO model Günther Zängl Deutscher Wetterdienst, Offenbach, Germany.
Earth Systems Science Chapter 6 I. Modeling the Atmosphere-Ocean System 1.Statistical vs physical models; analytical vs numerical models; equilibrium vs.
Cpt.UCLA Our work is motivated by two observations ‣ our understanding of cloud feedbacks is zonally symmetric. ‣ all pbl parameterizations strive to well.
Mechanisms of poleward propagating, intraseasonal convective anomalies in a cloud-system resolving model William Boos & Zhiming Kuang Dept. of Earth &
GFS Deep and Shallow Cumulus Convection Schemes
HWRF Model Sensitivity to Non-hydrostatic Effects Hurricane Diagnostics and Verification Workshop May 4, 2009 Katherine S. Maclay Colorado State University.
Basic Concepts of Numerical Weather Prediction 6 September 2012.
Coupled GCM The Challenges of linking the atmosphere and ocean circulation.
LINDSEY NOLAN WILLIAM COLLINS PETA-APPS TEAM MEETING OCTOBER 1, 2009 Stochastic Physics Update: Simulating the Climate Systems Accounting for Key Uncertainties.
A Look at High-Order Finite- Volume Schemes for Simulating Atmospheric Flows Paul Ullrich University of Michigan.
Zängl ICON The Icosahedral Nonhydrostatic model: Formulation of the dynamical core and physics-dynamics coupling Günther Zängl and the ICON.
1.Introduction 2.Description of model 3.Experimental design 4.Ocean ciruculation on an aquaplanet represented in the model depth latitude depth latitude.
A dual mass flux framework for boundary layer convection Explicit representation of cloud base coupling mechanisms Roel Neggers, Martin Köhler, Anton Beljaars.
Predictability of Seasonal Prediction Perfect prediction Theoretical limit (measured by perfect model correlation) Actual predictability (from DEMETER)
SRNWP Oct., 2003, Bad Orb Masaki Satoh and Tomoe Nasuno Frontier System Research for Global Change/ Saitama Inst. Tech. Radiative-convective equilibrium.
APE workshop at Univ. Reading, April 2005 Activity of K-1 Japan in APE Masahiro Watanabe (Hokkaido University) and Masahide Kimoto (CCSR, University.
Preliminary Results of Global Climate Simulations With a High- Resolution Atmospheric Model P. B. Duffy, B. Govindasamy, J. Milovich, K. Taylor, S. Thompson,
Convective Parameterization Options
Horizontal Mixing and Convection. 1st order prognostic PDE Q is the quadratic fluid dynamics term called the “Dynamical Core”. F is the Forcing “Physics”
A cell-integrated semi-Lagrangian dynamical scheme based on a step-function representation Eigil Kaas, Bennert Machenhauer and Peter Hjort Lauritzen Danish.
Sara Vieira Committee members: Dr. Peter Webster
ALADIN NH Recent progress Petra Smolíková, Radmila Brožková.
A Proposed Test Suite for Atmospheric Model Dynamical Cores Christiane Jablonowski University of Michigan, Ann Arbor, MI Contact Information: Christiane.
MJO simulations under a dry environment Marcela Ulate M Advisor: Chidong Zhang (… in a Nudging World)
A baroclinic instability test case for dynamical cores of GCMs Christiane Jablonowski (University of Michigan / GFDL) David L. Williamson (NCAR) AMWG Meeting,
Three Lectures on Tropical Cyclones Kerry Emanuel Massachusetts Institute of Technology Spring School on Fluid Mechanics of Environmental Hazards.
Forecast simulations of Southeast Pacific Stratocumulus with CAM3 and CAM3-UW. Cécile Hannay (1), Jeffrey Kiehl (1), Dave Williamson (1), Jerry Olson (1),
The status and development of the ECMWF forecast model M. Hortal, M. Miller, C. Temperton, A. Untch, N. Wedi ECMWF.
Simple tropical models and their relationship to GCMs Adam Sobel, Columbia Chris Bretherton, U. Washington.
CCSM Atmospheric Model Working Group Summary J. J. Hack, D. A Randall AMWG Co-Chairs CCSM Workshop, 28 June 2001 CCSM Workshop, 28 June 2001.
KoreaCAM-EULAG February 2008 Implementation of a Non-Hydrostatic, Adaptive-Grid Dynamics Core in the NCAR Community Atmospheric Model William J. Gutowski,
Frontier Research Center for Global Change Hirofumi TOMITA Masaki SATOH Tomoe NASUNO Shi-ichi IGA Hiroaki MIURA Hirofumi TOMITA Masaki SATOH Tomoe NASUNO.
Recent Developments in the NRL Spectral Element Atmospheric Model (NSEAM)* Francis X. Giraldo *Funded.
Implementation of Grid Adaptation in CAM: Comparison of Dynamic Cores Babatunde J. Abiodun 1,2 William J. Gutowski 1, and Joseph M. Prusa 1,3 1 Iowa State.
Workshop on Tropical Biases, 28 May 2003 CCSM CAM2 Tropical Simulation James J. Hack National Center for Atmospheric Research Boulder, Colorado USA Collaborators:
Georg A. Grell (NOAA / ESRL/GSD) and Saulo R. Freitas (INPE/CPTEC) A scale and aerosol aware stochastic convective parameterization for weather and air.
The MJO Response to Warming in Two Super-Parameterized GCMs
LMDZ Single Column Model + what is it ? + why is it interesting ? + List of 1D cases + how to install and run it ? M-P Lefebvre and LMDZ team.
On the mechanism of eastward-propagation of super cloud clusters (SCCs) over the equator – Impact of precipitation activities on climate of East Asia –
Bogdan Rosa 1, Marcin Kurowski 1 and Michał Ziemiański 1 1. Institute of Meteorology and Water Management (IMGW), Warsaw Podleśna, 61
Large-scale transient variations of tropical deep convection forced with zonally symmetric SSTs Zhiming Kuang Dept. Earth and Planetary Sciences and School.
A Thermal Plume Model for the Boundary Layer Convection: Representation of Cumulus Clouds C. RIO, F. HOURDIN Laboratoire de Météorologie Dynamique, CNRS,
Mass Coordinate WRF Dynamical Core - Eulerian geometric height coordinate (z) core (in framework, parallel, tested in idealized, NWP applications) - Eulerian.
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Component testing of the COSMO model’s turbulent diffusion.
Vincent N. Sakwa RSMC, Nairobi
Development of an Atmospheric Climate Model with Self-Adapting Grid and Physics Joyce E. Penner 1, Michael Herzog 2, Christiane Jablonowski 3, Bram van.
Developing General Circulation Models for Hot Jupiters
Tropical Atlantic SST in coupled models; sensitivity to vertical mixing Wilco Hazeleger Rein Haarsma KNMI Oceanographic Research The Netherlands.
Important data of cloud properties for assessing the response of GCM clouds in climate change simulations Yoko Tsushima JAMSTEC/Frontier Research Center.
Radiative-Convective Model. Overview of Model: Convection The convection scheme of Emanuel and Živkovic-Rothman (1999) uses a buoyancy sorting algorithm.
Status of CAM, March 2004 Phil Rasch. Differences between CAM2 and CAM3 (standard physics version) Separate liquid and ice phases Advection, sedimentation.
Emerging Research Opportunities at the Climate Modeling Laboratory NC State University (Presentation at NIA Meeting: 9/04/03) Fredrick H. M. Semazzi North.
A Proposed Test Suite for Atmospheric Model Dynamical Cores
The Met Office aqua-planet runs using pre-HadGAM1
Shifting the diurnal cycle of parameterized deep convection over land
Multiscale aspects of cloud-resolving simulations over complex terrain
Impact of the vertical resolution on Climate Simulation using CESM
Baroclinic and barotropic annular modes
ATOC 4720 class37 1. The vertically averaged divergence
National Center for Atmospheric Research
Outlines of NICAM NICAM (Nonhydrostatic ICosahedral Atmospheric Model)
Update on CAM and the AMWG. Recent activities and near-term priorities. by the AMWG.
Models of atmospheric chemistry
Presentation transcript:

Christiane Jablonowski and Diana Thatcher University of Michigan, Ann Arbor, USA Physics-Dynamics Coupling Workshop (PDC14), Ensenada, Mexico, 12/3/2014 Physics-Dynamics Test Strategies: Bridging the Gap with Simplified Moist Test Cases

The Talk at its Crossroads Effective Resolution: What should the scales be that the dynamical core passes to the physics (grid-point value, area-averaged, sub-sampled)? What are the believable scales in the dynamics? Test Strategies: Can we under- stand some aspects of the complex physics-dynamics coupling with simplified moist test cases? Partly covered by Peter Lauritzen’s talk Topic of this talk

Effective Resolution Papers with Foci on Advection Advertisement

Test strategies: It is important to be able to identify good coupling schemes from inferior ones early on in the development cycle. Once the theoretical analysis of the scheme is complete, how can further evidence be collected to ensure the chosen scheme performs as anticipated? The full NWP trial stage usually only offers limited scope for (costly) change. The difficulty is to design tests with sufficient signal and validity, without being too complex such that they are useful in the early development/evaluation phase. Physics-Dynamics Coupling: Session Announcements

Test Cases: Hierarchy with Increasing Complexity

Some Desirable Design Criteria Test cases should be designed for hydrostatic and non-hydrostatic dynamical cores on the sphere, ideally: for both shallow and deep atmosphere models be easy to apply: analytic initial data suitable for all grids formulated for different vertical coordinates deal with moisture in a simple way reveal information about the physics-dynamics coupling be as easy as possible, but as complex as necessary be cheap and easy to evaluate be relevant to atmospheric phenomena have a converged reference solution find broad acceptance in the modeling community

Overview of the Approaches Short-term deterministic assessments (15 days) –Moist baroclinic waves with large-scale condensation –Moist baroclinic waves coupled to the `simple-physics’ package by Reed and Jablonowski (James, 2012) Long-term ‘climate’ assessments (multiple years) –Moist version of the Held-Suarez test with elements of the `simple-physics’ package This talk’s goal: Convince you that idealized physics processes lead to reasonable atmospheric circulations. Long-term goal (partly covered in this talk): Evaluate whether idealized physics processes mimic the behavior of complex physics to aid our understanding.

Questions to Ask What is our motivation to pursue idealized approaches? Is it reasonable: How does a moist Held-Suarez (HS) aqua- planet simulation compare to a full-physics CAM5 aqua- planet simulation? Intercomparison: How do the different CAM5 dynamical cores compare in moist HS and complex aqua-planet experiments? Unit testing: How does the moist HS configuration compare to aqua-planet simulations that omit some processes (like the deep convection parameterization)? Can we replicate some aspects of the complex physics- dynamics interactions with the moist HS setup? What do we learn about the physics-dynamics coupling?

Motivation: Results from the Aqua-Planet Experiment (APE) Aqua-planet model intercomparison revealed a huge spread in the GCM circulations and precipitation characteristics Impossible to tell whether the APE differences are due to physics parameterizations or the dynamical cores or both? Our test approaches level the playing field (identical physics). Zonal-mean time-mean total precipitation rates (hemispherically averaged) in 16 GCMs in aqua-planet mode, see Blackburn at al. (2013)

DynamicsPhysics Process Variable Interaction Adding Simple Large-Scale Condensation to the Dynamical Core PBL mixing

Adding Simple Large-Scale Condensation Add a specific humidity field q and transport it as a tracer Compute condensation C tendencies to force q and the temperature T whenever the relative humidity (RH) at a grid point exceeds a threshold (e.g. RH > 100%): The large-scale precipitation P ls removes the water instantaneously without a cloud stage Reed and Jablonowski (James, 2012)

Baroclinic Wave: Moisture and Large-Scale Condensation Dynamical Core Model Intercomparison Project (DCMIP) 42 Large-scale condensation in a moist version of the Jablonowski-Williamson (2006) baroclinic wave leads to an intensification of the baroclinic wave here at day 9(DCMIP) 42 CAM-FV 1°x1° L30, dx = 110 km It rains in the right spots (updraft areas associated with frontal zones) Provides a first glimpse at the non-linear physics-dynamics interactions in the presence of moisture

DynamicsPhysics Process Variable Interaction Adding a Simple-Physics Package to the Dynamical Core Reed and Jablonowski (James, 2012) PBL mixing

Simple-Physics Package: Basic Ideas Replace the full-physics with a simple-physics package The simple-physics tendencies are The fluxes are either –the bulk aerodynamic surface fluxes (latent and sensible heat, friction) or –mimic the turbulence in the boundary layer via a first-order closure (K-theory with surface wind-speed dependent eddy diffusivities) C is large-scale condensation (no re-evaporation) Reed and Jablonowski (James, 2012)

Moist Interactions: Baroclinic Wave Dry Large-scale condensation Simple-Physics, no surface friction Complex CAM5 physics no surface friction Simple-Physics, with surface friction Complex CAM5 physics with surface friction Idealized moist baroclinic wave tests expose the behavior of simulations with complex physical parameterizations (here CAM5) Tests based on Jablonowski and Williamson (2006), Simple-physics: Reed and Jablonowski (2012) Surface pressure, day 9, CAM-FV 1°L30 hPa without radiation

DynamicsPhysics Variable Interaction Moist Version of the Held-Suarez Test on an Aqua-Planet (prescribed SST) Thatcher and Jablonowski (in prep.) Reed and Jablonowski (James, 2012) H H Held-Suarez (modified): Radiation: Newtonian Temperature relaxation Rayleigh friction (PBL momentum mixing and surface friction) Simple-Physics: Surface fluxes of latent sensible heat PBL mixing of moisture and temperature Large-scale condensation Color coding: PBL mixing

Moist Held-Suarez and Complex Aqua-Planet Thatcher and Jablonowski, in preparation Moist Held-Suarez with simple-physics Aqua-Planet with complex CAM5 physics CAM-SE 1° L30: Reasonable - Moist Held-Suarez mimics Aqua-Planet Temperature Zonal wind

Moist Held-Suarez and Complex Aqua-Planet Moist Held-Suarez with simple-physics Aqua-Planet with complex CAM5 physics CAM-SE 1° L30: Reasonable - Moist Held-Suarez mimics Aqua-Planet Thatcher and Jablonowski, in preparation Less efficient upward moisture transport, but distributions are similar Specific humidity Relative Humidity

Moist Held-Suarez and Complex Aqua-Planet CAM-SE 1° L30: Reasonable – Eddy transports are comparable Aqua-Planet with complex CAM5 physics Moist Held-Suarez with simple-physics Eddy heat flux Eddy kinetic energy

Moist Held-Suarez and Complex Aqua-Planet CAM-SE 1° L30: Reasonable – Physics forcing magnitudes comparable Aqua-Planet with complex CAM5 physics Moist Held-Suarez with simple-physics Deep convec- tion peaks higher up Focus on the tropics Large-scale condensation Temperature tendency Moisture tendency

Moist Held-Suarez and Complex Aqua-Planet Moist Held-Suarez with simple-physics Aqua-Planet with complex CAM5 physics CAM-SE 1° L30: Similar tropical waves are apparent in the total precipitation rate (averaged between 5S-5N) in moist Held-Suarez (top) and Aqua-Planet (bottom) runs (here eastward traveling Kelvin waves) Thatcher and Jablonowski, in preparation Precipitation is less organized in the moist HS experiment due to simplicity of precipitation mm/day Same Kelvin wave phase speeds

Moist HS, Complex Aqua-Planet & Unit Testing CAM-SE experiments with and without simple Betts-Miller (BM) and complex Zhang-McFarlane (ZM) deep convection Moist HS replicates complex Aqua-Planet (AP) behavior With deepNo deepTotal precipitation rate AP Moist HS BM deep ZM deep AP HS

Intercomparisons & Unit Testing Easier unit testing: How does CLUBB (new CAM PBL mixing, shallow convection, macrophysics) interact with the SE and SLD dycores and diffusion in CAM5 aqua-planet experiments? SE SLD Double versus single ITCZ Double ITCZ More diffusion

Intercomparisons: CAM5 dynamical cores The Community Atmosphere Model (CAM) provides four different dynamical cores (based on the primitive equations): 1.Semi-Lagrangian (SLD): two-time-level, semi-implicit semi- Lagrangian spectral transform model, Gaussian grid 2.Eulerian (EUL): three-time-level, semi-implicit Eulerian spectral transform dycore, Gaussian grid 3.Finite-Volume (FV): default dynamical core in CAM 5 & CAM 5.1, grid-point-based finite-volume discretization, explicit time- stepping scheme, latitude-longitude grid 4.Spectral Element (SE): new default dynamical core (CAM 5.3), based on continuous Galerkin spectral finite element method, designed for fully unstructured quadrilateral meshes (cubed- sphere grid), locally energy- and mass-conserving, explicit time-stepping scheme

Intercomparisons: CAM5 dynamical cores The kinetic energy (KE) spectra of the moist HS experiments replicate the KE spectra of the complex CAM5 aqua-planet runs (here with km grid spacing)

Intercomparisons: CAM5 dynamical cores Moist HS experiments can partly replicate the tropical precipitation rate characteristics of complex CAM5 aqua- planet runs Increased precip. Increased convergence Moist HS CAM5 Aqua-Planet CAM5 Aqua-Planet, no deep convection

Intercomparisons: CAM5 dynamical cores Meridional Eddy moisture transport: v’q’ Indication that the spectral dynamical cores EUL and SLD show systematic tropical differences in comparison to grid point models FV and SE in both moist HS and aqua-planet Moist HS Aqua-Planet SE EUL FV SLD

Conclusions The interactions between the dynamical core and moisture processes can already be simulated with very simple model configurations, like large-scale condensation, simple-physics, or the moist HS test Some aspects of the complex GCM behaviors can be replicated with the simplified physics setups Tests give access to an easier understanding of the physics- dynamics coupling Using identical physics with various dynamical cores levels the playing field Approach allows unit testing of selected parameterizations or tests of the physics-dynamics coupling technique Test cases hold promise to be useful for community use

Reed, K. A., and C. Jablonowski (2012), Idealized tropical cyclone simulations of intermediate complexity: a test case for AGCMs, J. Adv. Model. Earth Syst., Vol. 4, M04001, doi: /2011MS Jablonowski, C., and D. L. Williamson (2006), A Baroclinic Instability Test Case for Atmospheric Model Dynamical Cores, Quart. J. Roy. Met. Soc., Vol. 132, DCMIP shared workspace and DCMIP test case document: Thatcher, D. R. and C. Jablonowski, A moist variant of the Held- Suarez test for atmospheric model dynamical cores: Aquaplanet comparison and sensitivity analysis, manuscript in preparation References